Open Access

ARTICLE

Fine-Scale Velocity Measurement of High-Pressure Transient Multiphase Jets via Adaptive Feature Enhancement and Improved Window Deformation PIV

Jialei Jiang¹, Jiayuan Luo^2,3,*, Yan Su¹, Weiqiang Xiao¹, Jiajun Lu⁴, Haodong Liu⁵, Yuqi Huang²
1 Technology Centre, China Tobacco Zhejiang Industrial Co., Ltd., Hangzhou, China
2 College of Energy Engineering, Zhejiang University, Hangzhou, China
3 Huadian Electric Power Research Institute Co., Ltd., Hangzhou, China
4 Huzhou Institute of Industrial Control Technology, Huzhou, China
5 BYD Lithium Battery Co., Ltd., Shenzhen, China
* Corresponding Author: Jiayuan Luo. Email:
(This article belongs to the Special Issue: Thermal, Mass, and Life Management of Advanced Batteries and Fuel Cells)

Frontiers in Heat and Mass Transfer https://doi.org/10.32604/fhmt.2026.083123

Received 29 March 2026; Accepted 19 May 2026; Published online 15 June 2026

Abstract

Quantitative measurement of the high-speed gas-liquid-solid multiphase jets generated during the transient discharge of high-pressure vessels remains a significant challenge. Traditional Particle Image Velocimetry (PIV) techniques often fail in these scenarios due to the intense self-luminous interference, high transient velocities, and the absence of pre-seeded tracer particles. To address these issues, this paper proposes a robust non-intrusive measurement scheme integrating an adaptive image enhancement strategy with an improved cross-correlation algorithm. First, a preprocessing framework combining Contrast Limited Adaptive Histogram Equalization (CLAHE) and frequency-domain high-pass filtering is developed to suppress background noise and reconstruct fluid textures into high-contrast “pseudo-particle” features. Second, a multi-grid iterative cross-correlation algorithm incorporating window offset and window deformation techniques is established to enhance measurement accuracy in strong shear flows. The algorithm’s performance was rigorously validated using synthetic particle images and a theoretical Rankine vortex model. Results demonstrate that the proposed method achieves optimal accuracy for feature diameters of 1.5–3.0 pixels and maintains robust performance even under high noise levels (normalized noise intensity < 0.4). The method was subsequently applied to visualize the thermal runaway venting of an NCM18650 lithium-ion battery. The evolution of the jet velocity field was successfully captured, revealing a maximum projected velocity of visible jet features approaching 130 m/s during the violent multi-directional ejection phase. Furthermore, fine-scale shear vortex structures within the jet boundary layer were clearly resolved, verifying the algorithm’s capability to capture detailed flow topologies. This study provides an effective optical measurement solution for analyzing the dynamics of complex, high-speed multiphase flows in harsh environments.

---

Keywords

Particle image velocimetry (PIV); multiphase jet; image enhancement; window deformation; transient flow

---